Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 839 532 938 1 217 843 900 370 3 599 431 970 116 637 486 514 544 498 205 998
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 514 205 NA NA 970 498 486 839 431 544 938 NA 3 116 637 900 217 1 599 998 532 843 370
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 4 1 4 5 5 4 1 3 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "m" "c" "z" "x" "w" "B" "A" "I" "D" "Y"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 3 12 20
which( manyNumbersWithNA > 900 )
[1] 5 11 20
which( is.na( manyNumbersWithNA ) )
[1] 3 4 12
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 938 970 998
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 938 970 998
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 938 970 998
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "B" "A" "I" "D" "Y"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "m" "c" "z" "x" "w"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 2 8 10 11 15 16 17 18
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "small" NA NA "large" "small" "small" "large" "small" "large" "large" NA "small" "small" "large" "large" "small" "small" "large" "large" "large" "large" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "small" "UNKNOWN" "UNKNOWN" "large" "small" "small" "large" "small" "large" "large" "UNKNOWN" "small" "small" "large" "large" "small" "small" "large"
[20] "large" "large" "large" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 514 0 NA NA 970 0 0 839 0 544 938 NA 0 0 637 900 0 0 599 998 532 843 0
unique( duplicatedNumbers )
[1] 2 4 1 5 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 4 1 5 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE FALSE TRUE
which.max( manyNumbersWithNA )
[1] 20
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 998
which.min( manyNumbersWithNA )
[1] 18
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 1
range( manyNumbersWithNA, na.rm = TRUE )
[1] 1 998
manyNumbersWithNA
[1] 514 205 NA NA 970 498 486 839 431 544 938 NA 3 116 637 900 217 1 599 998 532 843 370
sort( manyNumbersWithNA )
[1] 1 3 116 205 217 370 431 486 498 514 532 544 599 637 839 843 900 938 970 998
sort( manyNumbersWithNA, na.last = TRUE )
[1] 1 3 116 205 217 370 431 486 498 514 532 544 599 637 839 843 900 938 970 998 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 998 970 938 900 843 839 637 599 544 532 514 498 486 431 370 217 205 116 3 1 NA NA NA
manyNumbersWithNA[1:5]
[1] 514 205 NA NA 970
order( manyNumbersWithNA[1:5] )
[1] 2 1 5 3 4
rank( manyNumbersWithNA[1:5] )
[1] 2 1 4 5 3
sort( mixedLetters )
[1] "A" "B" "c" "D" "I" "m" "w" "x" "Y" "z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 6.0 2.5 2.5 2.5 6.0 6.0 9.5 8.0 9.5 2.5
rank( manyDuplicates, ties.method = "min" )
[1] 5 1 1 1 5 5 9 8 9 1
rank( manyDuplicates, ties.method = "random" )
[1] 5 3 1 2 7 6 10 8 9 4
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.29060784 -0.10759068 0.35287341 0.72482112 1.05493648 0.26082794 2.09270437 -0.04721985 -0.45095058 0.41725214
round( v, 0 )
[1] -1 0 0 0 1 0 0 0 1 1 0 2 0 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.3 -0.1 0.4 0.7 1.1 0.3 2.1 0.0 -0.5 0.4
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.29 -0.11 0.35 0.72 1.05 0.26 2.09 -0.05 -0.45 0.42
floor( v )
[1] -1 -1 0 0 1 0 -1 0 0 1 0 2 -1 -1 0
ceiling( v )
[1] -1 0 0 1 1 1 0 1 1 2 1 3 0 0 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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